Background: Recent technological advances in mass spectrometry pose challenges in computational mathematics and statistics to process the mass spectral data into predictive models...
Michael Wagner, Dayanand N. Naik, Alex Pothen, Sri...
Time series data is common in many settings including scientific and financial applications. In these applications, the amount of data is often very large. We seek to support pred...
Background: Character mapping on phylogenies has played an important, if not critical role, in our understanding of molecular, morphological, and behavioral evolution. Until very ...
Background: Computational methods to predict transcription factor binding sites (TFBS) based on exhaustive algorithms are guaranteed to find the best patterns but are often limite...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...